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Studying the northern limit of winter wheat in the past, present and future in Huang-Huai-Hai Plain may provide theoretical basis and technical support to mitigate climate change on winter wheat cultivation in the sensitive zone in the North China. Daily meteorological data during 1961-2017 at 94 climatic stations in Huang-Huai-Hai Plain and the projected temperature during 2011-2100 generated by the Statistical Downscaling Model (SDSM4.2) and the second generation of Canadian Earth System Model (CanESM2) in representative concentration paths RCP4.5 and RCP8.5 scenarios were used in this study. Five climatic indicators, the coldest monthly mean temperature (≥-8 ℃), the extreme minimum temperature (≥-24 ℃), the accumulated temperature before overwintering (≥400 ℃), the negative accumulated temperature during overwintering (≥-450 ℃), and the accumulated temperature during the whole growth period of winter wheat(≥1 700 ℃), were used to evaluate the probabilities of winter wheat planting in different decades and the change of northern limit of winter wheat at 80% guarantee level in Huang-Huai-Hai Plain from 1961 to 2100. Main results were listed as following: during 1961-1970, the northern limit of winter wheat in Huang-Huai-Hai Plain was mainly distributed in the area of Tianjin-Bazhou-Baoding- Shijiazhuang-Xingtai-Linfen; during 1971-1980, it moved northwards by 65 km in Hebei province and 40 km in Shanxi province, respectively. Compared with 1971-1980, northern limit during 1981-1990 changed a little, it moved slightly southwards near Tangshan in Hebei province and northwards near Yuncheng in Shanxi province. Compared with 1981-1990, the northern limit during 1991-2000 showed a significant change, especially in Shanxi province, it gradually became a smooth parabola from a sine curve. After that, it just moved northward slightly during 2001-2010, then compared with 2001-2010, it showed a trend of moving southward during 2011-2017. Under RCP4.5 scenario, the spatial distribution of probabilities of winter wheat planting during 2011-2040, 2041-2070, 2071-2100 in Huang-Huai-Hai Plain and its surrounding areas were very similar, which decreased gradually from southeast to northwest, and the boundaries of interdecadal probabilities moved to northwest as time went on. The northern limit of winter wheat at 80% guarantee level mainly distributed in the area of Laoting-Tangshan- Beijing-Baoding-Shijiazhuang-Xingtai-Yushe-Linfen during 2011-2040. However, during 2041-2070, it moved to the area of Qinhuangdao in Hebei province and Jiexiu in Shanxi province. Besides, a non-planting zone about 13,600 km2 appeared near Yushe in Shanxi province. Compared with 2041-2070, northern limit during 2071-2100 tended to be stable in Hebei province and moved to the north of Taiyuan in Shanxi province. Under RCP8.5 scenario, the spatial distribution of probabilities of winter wheat planting in the next three periods were quite different, which mainly reflected in the boundaries of interdecadal probabilities of winter wheat planting, it moved to northwest obviously and became a curve liked “S”, while the northern limit of winter wheat at 80% guarantee level changed obviously. During 2011-2040, the northern limit of winter wheat was mainly distributed in the area of Qinhuangdao-Tangshan-Beijing- Baoding-Shijiazhuang-Linfen, then it moved northward to the area of Zunhua, Qinglong in Hebei province and Xingxian, Taiyuan in Shanxi province during 2041-2070, and the non-planting zone also appeared near Yushe in Shanxi province, however, the area reduced to 4 800 km2. During 2071-2100, the northern limit eventually arrived at the area of Chengde-Fengning-Zhangjiakou-Huailai-Baoding- Yuanping-Wuzhai-Hequ. In addition, compared with RCP8.5, the change trend of northern limit under RCP 4.5 scenario was smaller. It is an important measure to adjust the agricultural planting structure according to the influence of climate change. The study of the response of northern limit of winter wheat to climate change in Huang-Huai-Hai Plain and predicting its trend in the future can not only make rational use of potential resources and effectively avoid nature disasters in this region, but also has an important scientific significance and practical value for China’s food security. [ABSTRACT FROM AUTHOR]

In order to tackle climate change and improve the spatial-temporal collocation of water resources, the localization management was performed for the parameters of the Hargreaves model with reference evapotranspiration (ET0), which was calculated with the Penman-Monteith model using the daily meteorological data from 88 weather stations in Huang-Huai-Hai Plain during 1961-2010. The long series of daily temperature data from 2010 to 2100 in representative concentration paths RCP4.5 and RCP8.5 scenarios were simulated with the statistical downscaling model (SDSM4.2) and the second generation of Canadian Earth System Model (CanESm2). The long series of daily temperature data were used to calculate ET0 in the 21st century with the calibrated Hargreaves formula. The temporal change trend of ET0 during 1961-2100 was analyzed by the Mann-Kendall trend test and relative anomaly method, and the spatial distribution of ET0 during 2010-2100 was analyzed by the Kriging method in this study. Results indicated that the standard error of the corresponding parameter in the calibrated Hargreaves formula was very small, and the fluctuation range of correlation index between the calibrated Hargreaves model and the Penman-Monteith model was 0.65-0.85, with a mean value of 0.80, which indicated the high accuracy of the calibrated Hargreaves model. The determination coefficient of the maximum temperature and the minimum temperature between the observed and simulated values in the calibration period (1961-1990) and the verification period (1991-2005) was greater than 0.95, and the root mean square error was very small, indicating the high accuracy of the temperature simulated by the SDSM4.2. ET0 in the Huang-Huai-Hai Plain in 21st century under the 2 climate scenarios all had a trend of increasing in the future. The average values of ET0 under the RCP4.5 scenario in 2020 s, 2050 s and 2080 s were 940.71, 949.49 and 955.39 mm, respectively, 5.14%, 6.12% and 6.78% greater than the benchmark value (an average of 894.76 mm from 1961 to 2010). The average values of ET0 under the RCP8.5 scenario were 940.12 mm in 2020s, 966.72 mm in 2050 s and 986.97 mm in 2080s, respectively, 5.07%, 8.04% and 10.3% greater than the benchmark. The increase under RCP8.5 was slighter than that under RCP4.5, which was maybe caused by higher temperature and solar radiation under RCP8.5. From an overall perspective, the change trend of relative anomaly of mean temperature and ET0 was similar: most years before 2055 had negative anomaly, while after 2055 had positive anomaly. However, the value of positive and negative anomaly in ET0 had bigger fluctuations than that in mean temperature. The relative anomaly of mean temperature and ET0 increased gradually as time went on, and the increase of them under RCP8.5 was higher than that under RCP4.5. ET0 in the Huang-Huai-Hai Plain under RCP4.5 decreased gradually in a spoon-like curve from the border of Hebei, Shandong and Henan to the surrounding areas, and the minimum was observed in Tangshan and Laoting in Hebei, Dongtai in Jiangsu, and Zhumadian in Henan. The spatial distribution of ET0 under RCP8.5 in 2020 s was very similar to that in 2050 s, ET0 decreased gradually from the border of Hebei, Shandong and Henan to the surrounding areas, and the minimum was observed in Tangshan and Laoting in Hebei, Dongtai in Jiangsu, and Zhumadian in Henan. But there was a great difference in the spatial distribution of ET0 in 2080 s, especially for the spatial distribution of the greatest values. The maximum values were distributed in these areas in the Huang-Huai-Hai Plain: Huimin in Shandong, Xinxiang in Henan, Bengbu in Anhui and Xuyi in Jiangsu. The increase of ET0 would further aggravate the shortage of water resources in Huang-Huai-Hai Plain. This research provides valuable information for irrigation schedule. [ABSTRACT FROM AUTHOR]